#python #agent #chatgpt #claude #claude_3_opus #claude_api #docker #fly_io #gemini #gpt_4_api #groq #koyeb #langchain #mixtral_8x7b #python_telegram_bot #replit #replit_bot #telegram_bot #vertex_ai #zeabur

The TeleChat bot is a powerful Telegram bot that uses various large language model APIs, such as GPT-3.5, GPT-4, Claude, and Gemini, to provide efficient conversations and information searches. Here are the key benefits Supports a wide range of AI models, allowing you to switch between them easily.
- **Multimodal Question Answering** Works in group chats with features like topic mode and isolated dialogues.
- **Rich Plugin System** Allows flexible model switching and supports streaming output.
- **Efficient Message Processing** Available in English, Simplified Chinese, Traditional Chinese, and Russian.
- **Easy Deployment**: Supports one-click deployment on platforms like Koyeb, Zeabur, Replit, and Docker.

This bot enhances your Telegram experience by providing comprehensive and efficient interactions, making it a valuable tool for information gathering and conversation.

https://github.com/yym68686/ChatGPT-Telegram-Bot

#jupyter_notebook #ai #finetuning #langchain #llama #llama2 #llm #machine_learning #python #pytorch #vllm

The `llama-recipes` repository helps you get started with Meta's Llama models, including Llama 3.2 Text and Vision. It provides example scripts and notebooks for various use cases, such as fine-tuning the models and building applications. You can use these models locally, in the cloud, or on-premises. The repository includes guides for installing the necessary tools, converting models to Hugging Face format, and using features like multimodal inference and responsible AI practices. This makes it easier for you to quickly set up and use the Llama models for your projects, saving time and effort.

https://github.com/meta-llama/llama-recipes

#jupyter_notebook #gemini #gemini_api #generative_ai #google #google_cloud #google_gemini #langchain #llm #palm_api #vertex_ai #vertex_ai_gemini_api #vertexai

This repository helps you use and develop generative AI with Google Cloud. It includes notebooks, code samples, and apps for various tasks like image generation, chatbots, and language models. You can find resources for building search engines, conversational AI, and more using Vertex AI. The repository also provides setup instructions and learning materials. This helps you quickly start and manage generative AI projects, making it easier to create innovative solutions.

https://github.com/GoogleCloudPlatform/generative-ai

#go #ai #go #golang #langchain

LangChain Go is a tool that helps you build applications using large language models (LLMs) with the Go programming language. It makes it easy to use LLMs by allowing you to combine different parts of your application in a flexible way. This means you can create smart programs that can answer questions, generate text, and more, all within your Go code. The benefit to you is that you can quickly and easily integrate powerful AI capabilities into your projects without needing to learn complex new technologies. There are also many examples and resources available to help you get started.

https://github.com/tmc/langchaingo

#python #ai_gateway #anthropic #azure_openai #bedrock #gateway #langchain #llm #llm_gateway #llmops #openai #openai_proxy #vertex_ai

LiteLLM is a tool that helps you use different AI models from various providers like OpenAI, Azure, and Huggingface in a simple way. Here’s how it benefits you You can call any AI model using a consistent format, making it easier to switch between different providers.
- **Consistent Output** You can set budgets and rate limits for your projects, helping you manage costs and usage efficiently.
- **Retry and Fallback Logic** It supports streaming responses and asynchronous calls, which can improve performance.
- **Logging and Observability**: You can easily log data to various tools like Lunary, Langfuse, and Slack, helping you monitor and analyze your AI usage.

Overall, LiteLLM simplifies working with multiple AI providers, makes your code cleaner, and helps you manage resources better.

https://github.com/BerriAI/litellm

#typescript #agent_monitoring #analytics #evaluation #gpt #langchain #large_language_models #llama_index #llm #llm_cost #llm_evaluation #llm_observability #llmops #monitoring #open_source #openai #playground #prompt_engineering #prompt_management #ycombinator

Helicone is an all-in-one, open-source platform for developing and managing Large Language Models (LLMs). It allows you to integrate with various LLM providers like OpenAI, Anthropic, and more with just one line of code. You can observe and debug your model's performance, analyze metrics such as cost and latency, and fine-tune your models easily. The platform also offers a playground to test and iterate on prompts and sessions, and it supports prompt management and automatic evaluations. Helicone is enterprise-ready, compliant with SOC 2 and GDPR, and offers a generous free tier of 100k requests per month. This makes it easier to manage and optimize your LLM projects efficiently.

https://github.com/Helicone/helicone

#typescript #artificial_intelligence #chatbot #chatgpt #javascript #langchain #large_language_models #llamaindex #low_code #no_code #openai #rag #react #typescript #workflow_automation

Flowise is a tool that makes it easy to build applications using Large Language Models (LLMs) with a drag-and-drop interface. You can quickly start by installing NodeJS and then installing Flowise using simple commands. It also supports deployment through Docker and various cloud services like AWS, Azure, and more. The benefit to you is that you can create customized LLM flows without needing to write complex code, making it easier and faster to develop your applications. Additionally, Flowise offers extensive documentation and community support to help you along the way.

https://github.com/FlowiseAI/Flowise

#typescript #agent #agents #ai #ai_agent #ai_assistant #assistant #copilot #copilot_chat #hacktoberfest #langchain #langgraph #llm #nextjs #open_source #react #reactjs #ts #typescript

CopilotKit helps you build smart AI assistants that work directly within your applications. These assistants can analyze data, manage transactions, plan trips, and even help with research, all through natural language interaction. You can get started quickly with their easy-to-follow documentation and code samples. Joining their Discord community also gives you access to support and resources from the team and other users. This makes it easier for you to create powerful AI tools that assist your users in various tasks, enhancing their experience and productivity.

https://github.com/CopilotKit/CopilotKit

#python #agents #ai #artificial_intelligence #attention_mechanism #chatgpt #gpt4 #gpt4all #huggingface #langchain #langchain_python #machine_learning #multi_modal_imaging #multi_modality #multimodal #prompt_engineering #prompt_toolkit #prompting #swarms #transformer_models #tree_of_thoughts

Swarms is an advanced multi-agent orchestration framework designed for enterprise-grade production use. Here are the key benefits and features Swarms offers production-ready infrastructure with high reliability, modular design, and comprehensive logging, reducing downtime and easing maintenance.
- **Agent Orchestration** Swarms allows multi-model support, custom agent creation, an extensive tool library, and multiple memory systems, providing flexibility and extended functionality.
- **Scalability** Swarms includes a simple API, extensive documentation, an active community, and CLI tools, making development faster and easier.
- **Security Features**//docs.swarms.world) for more detailed information.

https://github.com/kyegomez/swarms

#python #chatgpt #langchain #llm #openai #openai_chatgpt #python #ui

Chainlit is a free and open-source Python framework that helps developers build advanced Conversational AI applications quickly. With Chainlit, you can create scalable and production-ready AI apps in minutes, not weeks. It provides full documentation, a community for help, and many examples to get you started. You can install it easily using `pip install chainlit` and start building your own apps right away. This saves you a lot of time and effort, making it easier to develop powerful AI applications.

https://github.com/Chainlit/chainlit